Development and validation of a multifactorial nomogram to predict 48 month mortality in decompensated heart failure.

BACKGROUND AND AIMS: As the incidence of heart failure (HF) increases, the need for practical tools to evaluate the long-term prognosis in these patients remains critical. Our study aimed to develop a 48 month prediction model for all-cause mortality in decompensated HF patients using available clinical indicators. METHODS: HF patients (n = 503), 60 years or older, were divided into a training cohort (n = 402) and a validation cohort (n = 101). Data on demographics, comorbidities, laboratory results and medications were gathered. Prediction models were developed using the Prognostic Nutritional Index (PNI), cholinesterase (ChE) and a multifactorial nomogram incorporating clinical variables. These models were constructed using the least absolute shrinkage and selection operator algorithm and multivariate logistic regression analysis. The performance of the model was assessed in terms of calibration, discrimination and clinical utility. RESULTS: The mean age was 77.11 ± 8.85 years, and 216 (42.9%) were female. The multifactorial nomogram included variables of ChE, lymphocyte count, albumin, serum creatinine and N-terminal pro-brain natriuretic peptide (all P < 0.05). In the training cohort, the nomogram's C-index was 0.926 [95% confidence interval (CI) 0.896-0.950], outperforming the PNI indices at 0.883 and ChE at 0.804 (Z-tests, P < 0.05). The C-index in the validation cohort was 0.913 (Z-tests, P < 0.05). Calibration and decision curve analysis confirmed model reliability, indicating a more significant net benefit than PNI and ChE alone. CONCLUSIONS: Both the ChE- and PNI-based prediction models effectively predict the long-term prognosis in patients over 60 years of age with decompensated HF. The multifactorial nomogram model shows superior performance, improving clinical decision-making and patient outcomes.

The Combined Use of Orf Virus and PAK4 Inhibitor Exerts Anti-tumor Effect in Breast Cancer.

The parapoxvirus Orf virus (ORFV) has long been recognized as one of the valuable vectors in researches of oncolytic virus. In order to develop a potential therapeutic strategy for breast cancer based on the oncolytic virotherapy via ORFV, firstly we explore the oncolytic effects of ORFV. Our research showed that ORFV exerts anti-tumor effects in vitro by inducing breast cancer cell G2/M phase arrest and cell apoptosis. In vivo experiments were carried out, in which we treated 4T1 tumor-bearing BALB/C mice via intratumoral injection of ORFV. ORFV can exert anti-tumor activity by regulating tumor microenvironment (TME) and inducing a host immune response plus directly oncolytic effect. The CRISPR-Cas9 knockout library targeting 507 kinases was used to screen out PAK4, which is beneficial to the anti-tumor effect of ORFV on breast cancer cells. PF-3758309 is a potent PAK4-targeted inhibitor. Co-using of ORFV and PF-3758309 as a combination treatment produces its anti-tumor effects through inhibition of cell viability, induction of apoptosis and suppression of cell migration and invasion in vitro. The results of in vivo experiments showed that the tumor growth of mice in the combination treatment group was significantly inhibited, which proved that the combination treatment exerts an effective anti-tumor effect in vivo. In summary, we have clarified the oncolytic effect of ORFV on breast cancer, and found that the combination of ORFV and PAK4 inhibitor can effectively improve the oncolytic effect of ORFV. We hope our research could provide a new idea for the development of new treatment strategies for breast cancer.

Preclinical efficacy and involvement of mTOR signaling in the mechanism of Orf virus against nasopharyngeal carcinoma cells.

AIMS: Orf virus (ORFV) is a parapoxvirus causing contagious ecthyma in sheep and goats. With inhibitory role of ORFV reported by previous studies, ORFV can be a candidate of oncolytic virus. However, few studies reported the application and mechanism of ORFV in nasopharyngeal carcinoma (NPC). We aimed to elucidate the anti-tumor mechanism of ORFV against NPC cells. MATERIALS AND METHODS: The anti-tumor effect of ORFV in NPC cells was confirmed by cell counting kit 8 (CCK-8) assay, flow cytometry and Western blot. In vitro and in vivo experiments were adopted to evaluate the inhibitory effect of ORFV in NPC cells. Western blot was used to determine the down-regulation of rapamycin (mTOR) signaling and autophagy enhancement induced by ORFV. To explore the mechanism of ORFV on NPC cells, mTOR signaling agonist and autophagy inhibitors were used to rescue the effects of ORFV. KEY FINDINGS: The results indicated that ORFV replicates in NPC cells, thus induces the apoptosis of NPC cells. Moreover, ORFV can effectively inhibit NPC cell growth in vivo. ORFV infection in NPC cells leads to the mTOR signaling inhibition and up-regulated autophagy, which might be the specific mechanism of ORFV in killing tumor cells. As to safety confirmation, normal nasopharyngeal epithelial cells NP69 are insensitive to ORFV. More importantly, ORFV would not cause organ damage in vivo. SIGNIFICANCES: Our data clarified that ORFV induces autophagy of NPC cells via inhibiting mTOR signaling, thus further inducing apoptosis. The anti-tumor role of ORFV might provide a preclinical strategy for NPC treatment.

Identification of in vitro and in vivo oncolytic effect in colorectal cancer cells by Orf virus strain NA1/11.

Orf virus (ORFV) is a favorable oncolytic viral carrier in research, and ORFV strain NZ2 has been revealed to have antitumor effects in animal models mediated by immunoregulation profile. However, the antitumor effects triggered by the ORFV in colorectal cancer (CRC) cells is poorly characterized. The in vivo and in vitro roles of ORFV in CRC were determined using western blotting, colony formation, CCK­8, wound scratch assay, qPCR, and animal models. Furthermore, cytokine antibody chip assay, flow cytometry, western blotting, and immunohistochemical (IHC) assays were conducted to explore the potential mechanism of ORFV. The present data revealed that ORFV strain NA1/11 infected and inhibited the in vitro growth and migration of CRC cells. By establishing a CRC model in Balb/c mice, it was revealed that ORFV strain NA1/11 significantly inhibited the in vivo growth and migration of CRC cells. A cytokine antibody array was utilized to obtain a more comprehensive profile revealing the differentially expressed cytokines in ORFV infection. Cytokines, such as IL­7, IL­13, IL­15, CD27, CD30, pentraxin 3, and B lymphocyte chemoattractant (BLC), were upregulated. Axl, CXCL16, ANG­3, MMP10, IFN­Î³ R1 and VEGF­B were downregulated. The results indicated that ORFV played roles in the regulation of key factors relevant to apoptosis, autoimmunity/inflammation, angiogenesis, and the cell cycle. Finally, data was presented to validate that ORFV infection induces oncolytic activity by enhancing apoptosis in vivo and in vitro. In conclusion, ORFV could be an oncolytic virus for CRC therapy.

Collagen family genes and related genes might be associated with prognosis of patients with gastric cancer: an integrated bioinformatics analysis and experimental validation.

BACKGROUND: Gastric cancer (GC) is disease with a high morbidity. The purpose of this study was to identify genes essential to GC development in patients and to reveal the underlying mechanisms of progression. METHODS: Bioinformatics analysis is an effective tool for discovering essential genes of different disease states. We used the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs), the DAVID online tool to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs, the STRING database to construct the protein-protein interaction (PPI) network of DEGs, the Oncomine and the Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) databases to analyze the gene expression differences, the Human pan-Cancer Methylation database (MethHC) to compare the DNA methylation of genes, and the Kaplan-Meier plotter to show the survival analysis of DEGs. We performed Real-Time quantitative PCR (RT-qPCR) experiment to confirm our analysis results. RESULTS: After the integration of four Gene Expression Series (GSEs), we identified 407 DEGs. GO and KEGG pathway analysis indicated that the upregulated DEGs were significantly enriched in Extracellular Matrix (ECM) related functions and pathways. The main DEGs were collagens (COLs). Moreover, the downregulated DEGs were enriched in ethanol oxidation. Several groups of DEGs, such as insulin-like growth factor binding protein (IGFBP), collagen (COL) and serpin peptidase inhibitors (SERPIN) gene families, constituted several PPI networks. In the Oncomine database, all of the collagen genes were highly expressed in breast cancer, esophageal cancer, GC, head and neck cancer and pancreatic cancer, compared with normal tissues. Consistently, from the TCGA-STAD database, most of the collagens (COLs) were highly expressed and exhibited methylated variation in GC patients. In GC patients, some of these collagen (COL) genes related to worse prognosis, as evidenced by the results from the Kaplan-Meier plotter database analysis. Our RT-qPCR results showed that collagen type III α1 chain (COL3A1) was highly expressed in GC cells. Collagen type V α1 chain (COL5A1) was highly expressed, except in AGS cells, which was consistent with our analysis. CONCLUSIONS: Collagen (COL) family genes might serve as progression and prognosis markers of GC.